Canada Proves To Be Fertile Ground For Global Push Into Advanced AI Research
By December 14, 2017– Published in on
DeepMind is an interesting company.
The illustrious Elon Musk bought a chunk of it after Google, now called Alphabet, took majority control of DeepMind in 2014. Mr. Musk claims that his purchase was made so that he could keep an eye on what he views as the biggest threat to humanity in the history of our existence, though the billionaire entrepreneur has been known to make exaggerations from time to time.
What DeepMind does, in a holistic sense, is something of a mystery. While they are owned by a publicly traded company, much of what goes on inside of the company is shrouded in secrecy. This is understandable given the nature of the space they are working in, though it has also caused some amount of public outcry in its native England.
Regardless of the specifics, it is difficult to push the technological envelope and stay within the bounds of public morality. Many doctors faced criticism of early dissension techniques performed on human cadavers, though the anatomical knowledge they gained was invaluable for the progression of medical science.
This is similar to the kind of criticism that DeepMind has faced in England in the NHS data sharing affair, but when we examine the potential that Machine Learning (ML) has for medical diagnostics, it should be apparent that contemporary privacy concerns may be getting in the way of big data based breakthroughs that could save millions of lives.
Up to this point, the most public demonstrations of what DeepMind does have been games between their learning programs, and a variety of human competitors.
AlphaGo was their first known foray into the world of Go, which is an Asian game that is very difficult for AI to adapt to. But for AlphaGo, defeating a string of professional Go players was no problem, and recently a next generation Go program called AlphaGo Zero beat its predecessor after only three days of play.
The underlying idea is that these programs are able to learn via external inputs, and by using advanced data analysis, find solutions to problems, or detect patterns that a human may miss. This is where big data and DeepMind could contribute so much to diagnostics across a variety of industries, and also where their recent expansion into Canada comes into play.
According to a range of reputable sources, there are nearly a dozen graduates from the University of Alberta (UoA) on staff at DeepMind. This may be one of the reasons why Alphabet decided that the UoA would be a good place to open the first ever DeepMind office outside of England, but some of the staff at the UoA may be another factor in their move into Edmonton.
Rich Sutton was the first adviser to DeepMind, and he is currently a professor at the UoA. Michael Bowling and Patrick Pilarski also may have had a hand in teaching some of the current staff at DeepMind, so it would make sense that these three professors have been chosen to head up DeepMind Alberta. Patrick Pilarski is an especially interesting addition, as he has done extensive work in how machine learning, robotics and predictive diagnostics could be deployed into healthcare.
A Supportive Environment
It came as a surprise to many that DeepMind chose Canada over the USA for its first venture outside of the UK, but there are many good reasons why Canada makes a lot of sense when it comes to high tech development.
In the wake of President Trump's travel ban, and prejudice against permitting highly skilled foreign scientists to work in the USA, Canada looks a lot more like the perfect place in North America for the next tech revolution to find its base.
While the tech sector and Silicon Valley have been agnostic at best towards the Trump administration, the relationship between Alphabet boss Eric Schmidt and Prime Minister Trudeau looks pretty cozy based on their recent public dialog. Given the investment that Alphabet, via DeepMind, is making in Canada, it would appear that there is a real drive to push the Canadian tech sector up a few notches.
While AI and ML are still in their infancy as a commercial technologies, they are developing at a rapid clip. It seems like today many cutting edge technologies dovetail perfectly together, and with these kinds of overlapping capabilities, almost anything is possible.
DeepMind's incredible analytical ability could function with next generation biochemical diagnostic tests to screen people for diseases like diabetes, and save many people from a lot of health trouble, not to mention the reduced costs for the healthcare system. And this example is just scratching the surface of what is possible to imagine, today.
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In addition to ML and AI, technologies like VR/AR, Blockchain and cryptocurrencies will be on the agenda. The conference will be taking place at the Metro Toronto Convention Center, in Toronto, on January 31st. Registration is now open, and if you preregister, or are a student, there are reduced prices available.
It should be very clear from Alphabet's decision to integrate the UoA at the formative levels of DeepMind's future development, that technological breakthroughs and education are truly inseparable. We are glad to be helping to create opportunities for some of the most forward thinking people in the world to meet face to face. So have a look at who is attending Cantech, and think about how connections could make your ideas come to life!